342 papers
The intersection of physics and biology, often called biophysics, explores how the fundamental laws of nature govern living systems. This dynamic field applies physical principles to understand everything from the movement of single molecules to the complex mechanics of cells, revealing the invisible forces that drive life itself.
Gist.Science monitors the arXiv preprint server daily to bring you the freshest research in this category. For every new submission, we provide both a clear, plain-language overview and a detailed technical summary, making cutting-edge science accessible to everyone regardless of their background.
Below are the latest papers added to our collection, offering a fresh look at how physics illuminates the biological world.
This paper presents a nonlinear analytical theory derived via asymptotic analysis to explain how non-reciprocal chemical interactions and cellular heterogeneity govern the robust spatial organization and dynamical regimes of migrating cell collectives, specifically predicting a balanced mixing and localization mechanism in dendritic and T-cell co-migration driven by intermediate long-range chemoattractant signaling.
This paper presents exact finite-size expressions and a scalable combinatorial framework for characterizing equilibrium cluster statistics in cooperative and anticooperative binding on finite one-dimensional rings, providing new benchmarks for understanding spatial organization in small periodic systems relevant to biological assemblies.
This paper demonstrates that inhomogeneous polymers driven by temporally patterned active processes can achieve specific conformations and strong compaction through tension-mediated coupling of distant loci, where delayed excitations induce coherent motion and folding.
This paper presents a numerical study of a three-layer stochastic autocatalytic system demonstrating that hierarchical organization drives maximum entropy production and genetic entropy reduction while exhibiting significantly looser thermodynamic uncertainty and speed limit bounds compared to minimal models, ultimately establishing a formal correspondence between such evolutionary dynamics and diffusion-model training.
This paper argues that standard planktonic antimicrobial assays fail to capture the complex, depth-stratified dynamics of chronic biofilm infections and proposes a new four-dimensional, live, label-free imaging framework to better evaluate antimicrobial efficacy within mature biofilms.
This study employs modern coupled-cluster methods, including pair coupled cluster doubles (pCCD) variants, to model the catalytic mechanism of molybdenum cofactor (Moco) variants with DMSO and NO substrates, revealing the critical roles of structural relaxation, environmental effects, and orbital-based quantum information in elucidating reaction energetics and bond formation.
This paper introduces a thermodynamically informed, temperature-transferable machine-learned coarse-grained framework for proteins that explicitly decomposes the potential of mean force into energetic and entropic components, enabling accurate prediction of temperature-dependent properties like heat capacity across different thermal regimes without retraining.
This paper introduces an information-theoretic framework that optimizes the selection of representative conformations in cryo-electron microscopy by maximizing mutual information between ensemble weights and images, thereby defining a measurement-induced coarse-graining that balances structural resolution with statistical identifiability in the presence of noise.
This paper explores the theoretical implications of using hierarchical Markov models to describe animal behavior, demonstrating how the models' eigenvalues and eigenvectors provide interpretable time scales and modifications to clarify the sequence-like nature, predictability, and effective dimensionality of behavior.
This paper bridges engineering and biology to explore how advanced bioelectrical interfaces can be used to study and manipulate endogenous electrical signals in non-excitable cells, offering new avenues for controlling gene expression, reprogramming cancer, and intervening in aging.